Madrigal 发表于 2025-3-26 21:30:34
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Thomas Witelski,Mark Bowenlumn sum-based histogram modeling function is devised to separate the left and right knee from X-ray image. Later DNN-based five-class classification is applied to identify the severity grade. To achieve this, we have developed our own convolutional neural network named OACnet (Osteoarthritis classi下垂 发表于 2025-3-27 13:08:23
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Thomas Witelski,Mark Bowencal practitioner considers computer-based detection as second opinions. This paper focused on cluster analysis using K-means and classification of breast cancer in the pathological image. The proposed method helps to classify histopathology image in four class by using Support Vector Machine with th业余爱好者 发表于 2025-3-27 20:32:22
Thomas Witelski,Mark Bowen mm and two levels of diffusion sensitization (.). MATLAB 2014 Simulink software was used for the data analysis. The Region of Interest (ROI) the brain lesion was selected. The mean values of both the skewness and kurtosis of ADC within the ROI were determined and finally, the values were compared b变态 发表于 2025-3-28 00:57:06
of uncertain expert systems, deep learning models, microarray analysis, and multi-classifier approaches to enhance breast cancer diagnosis and prognosis prediction. The findings of this research have significant implications for healthcare. SVM and Random Forest, as machine learning techniques, canfiscal 发表于 2025-3-28 05:52:35
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Thomas Witelski,Mark Bowensifier gives 82.85% recognition accuracy using Histogram of Oriented Gradient method. The dataset containing 4390 words collected from more than 100 writers. The second phase focuses on digitization and transliteration of recognized words and conversion of transliterated text into speech, which is u